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Erosion has become one of the serious problems in recent years as the degradation of the valuable natural resource of soil is a major ecological threat that can cause various environmental issues. The primary objective of this study is to identify the suitable sediment yield (SY) model for the Ponnaniyar river basin in Trichy city, India using CHIRPS dataset and to determine the severely affected sub-watersheds (SWs) within the study area. Using RUSLE model, the erosion rate in ungauged basin i.e. Ponnaniyar river basin is calculated which ranges between 0 and 2690.72 tons/ha/year. The results reveal that the total quantity and mean soil loss of the whole basin are found to be 3,907,005.56 tons/year and 22.66 tons/ha/year, respectively. The SY of Ponnaniyar river basin is calculated using SDR model (varies from 0 to 443.97 tons/ha/year) and MUSLE model (varies from 0 to 358.24 tons/ha/year). In this study area, the mean and total quantity of sediment yield using SDR model found to be 3.57 tons/ha/year and 850,650.47 tons/year, respectively while in the MUSLE model the mean sediment yield and total quantity found to be 3.82 tons/ha/year and 688,910.17 tons/year, respectively. Based on ROC curve analysis, the SDR model is identified to be the suitable SY model for the Ponnaniyar river basin with an accuracy value of 0.752, while the MUSLE model has an accuracy value of 0.652, which is slightly lower than SDR. Using SDR model, the highly susceptible SWs are identified as SW11, followed by SW2 and SW 9 with mean sediment yield of 14.4, 11.98, 10.61 tons/ha/year, respectively. This study provides a exhaustive evaluation of soil loss and yield, determining the high priority SWs that could be useful in developing effective soil management practices to decrease soil loss and yield. Additionally, the study recommends the establishment of a hydrometric station in Ponnaniyar river basin to observe the streamflow and sediment yield, in order to prevent soil loss during flash flooding.

The importance in studying issues like heat waves, urban heat islands, and polluted air, is on the rise in the perspective of global warming. One effective method to mitigate the hot climate in urban areas is by harnessing the cooling effect of rivers. This study aims to examine the impact of the Krishna River on its surrounding urban environment by utilizing geospatial techniques in identifying and analysing the surface temperature and urban morphology data. Additionally, it seeks to explore the potential of rivers in cooling urban areas using linear regression models. The findings of this study indicate the following key points. Initially, it is noteworthy that aqueous entities possess a cooling impact on the adjacent environment. The maximum range of this cooling influence is observable at 2,000 m, while the most favourable distance is at 1200–1400 m. Since the stretch of the river in the study area was divided with a barrage as upstream and downstream, the river cooling effect is clear in the upstream side as it contains water when compared to the downstream side with dry sand. The findings indicate a correlation between elevation in the Normalised Difference Vegetation Index and a reduction in Land Surface Temperature (LST), as evidenced by negative correlation. Moreover, an elevation in the Built-Up Index results in reduction in Land Surface Temperature (LST) values. With regards to the Sky View Factor, it is generally observed that higher values are associated with elevated Land Surface Temperature (LST), except in regions where air circulation is enhanced, leading to a reduction in temperatures. The results give the view over possibility of measures that can be itaken to sustain the urban environment and reduce the impact of the heat island effect. Examples include increasing the amount of urban vegetation and reducing the density of buildings. The findings of this study provide important empirical facts and instructive examples to support the efforts of urban planning and development organizations in improving the urban environment and creating sustainable urban habitats.

Floods are a natural calamity that causes loss of human life and destruction of property. They are caused by riverine, coastal and storm surges, cyclones, and tsunami waves. The primary causes of urban floods are an unusual rise in quantum of rainfall, extreme man-made changes in land-use–land-cover patterns, and consequent detrimental hydrological impacts. There are different methods available for flood estimation like rational formulae and empirical methods for approximate estimation of flood peak discharge, but they cannot be applied widely, and their application is confined to a particular region. The current study first discusses the causes of urban floods and then assesses the appropriate flood modeling methods that can be effectively used for urban catchments. Flood modeling methods deployed internationally and nationally in major- and medium-sized cities are discussed, and the research gap is identified. The advantages and demerits of each method are analyzed, and the parameters involved are also identified. An integrated modeling approach is chosen for this case study. In India, only coastal megacities have been considered for flood modeling studies thus far. There have been no research studies conducted on medium-sized urban catchment areas using an integrated modeling approach. Therefore, the present article reviews all the features of a novel integrated flood modeling approach which can be adopted for a medium-sized dendritic pattern ungauged urban catchment area.

The main objective of the present study is to enhance the accessibility facilities for local public to educational centers in Tiruchirappalli City. For this approach, the existing K-12 schools, Census tracts and road network were spatially plotted using the techniques of geospatial system. Spatial accessibility index is computed using Three-step floating catchment area (3SFCA) method. The findings indicate (39%) of catchment area has been shortage of education facilities. The index of 3SFCA and its spatial pattern has been compared, validated using enhanced two-step floating catchment area (E2SFCA) method. The incorporated Gaussian weight of 3SFCA clearly reduces the high estimate of demand problem of the study area. Through 3SFCA and E2SFCA, the number of wards observed to be shortage is 14 and 26 respectively. Overall, the analysis concludes that 3SFCA is an effective method in spatial planning of educational facilities. In future, this study enables the urban planners and decision makers to maximize spatial accessibility by establishing a new facility and improve the existing facilities in shortage region.

Fast economic development and expansive urban growth necessitates an urban development agenda that emphasis on adequate urban open space facility spatial planning and developmental initiatives aimed at ensuring proximity and accessibility to essential urban facilities for all urban residents. Locating suitable site in the disparity region for open space facilities such as parks and playgrounds enhances the quality of citizen’s life. To address the necessitating concern of the existing trend of uneven distribution, the Gravity-based spatial accessibility model i.e. Three-step floating catchment area method is opted to identify the derprived region and Multi-criteria decision analysis model is used to locate optimum site in the deprived region. Tiruchirappalli city has 37 parks and 14 playgrounds, out of which 14 parks closed due to improper maintenance. Among the 65 wards, it was observed that 33 wards had no accessibility to parks within the threshold distance of 3 km with the 73.5% of the city population. The questionnaire of 821 samples was collected in both well-served region and unserved region of parks and playgrounds facilities, it states that the 82% of residences in well-served region residents access frequently whereas only 23% of residences access in the unserved region. Hence, to maximize the accessibility, the new open space can be provided in the optimum sites obtained by Analytical Hierarchy Process that shows the area of 7.68 km2as very highly suitable category and 48.48 km2as highly suitable category. Thereby it becomes important to focus on proper spatial planning of urban facilities and transportation services needed for the establishment of an efficiently functioning city.

The primary factor governing the accuracy of the vibration test is the sensor placement. Positioning of sensors for conducting the modal analysis test must be done with utmost care. Conducting a trial test on massive structures like dams, bridges, high-rise buildings, etc. is generally challenging and expensive. With the availability of advanced finite element software packages, it is possible to simulate models and obtain satisfactory and reliable results. Therefore, a pretest planning of sensor positions can be done, based on results obtained from finite element analysis. There are only limited number of earlier studies in the field of optimization of sensors for Structural Health Monitoring of civil engineering structures. In the practice of Vibration-based Structural Health Monitoring of structures, in order to detect both bending and twisting modes, the common practice is to fix the sensors on both sides of the structure and at equal spacing. When the sensors are placed in this fashion, there might be sharing of information between adjacent sensors, thus unnecessarily escalating the instrumentation cost. Sensor optimization helps in reducing the cost of instrumentation and maximizing the individuality in the information obtained from the sensors. The current study utilizes multiple criteria-based sensor optimization for Structural Health Monitoring of a bridge. The optimization strategy utilizes two criteria: (i) Triaxial Effective Independence and Threshold of Redundancy, in order to ensure the individuality in the information gathered from the sensors. Based on the above criteria, it was found that for a redundancy value of 0.60, 27 accelerometers were required for observing 12 modes. As the optimization strategy involves a least square estimation, it was observed that when the sensors were increased beyond 25, the condition number of Fisher Information Matrix (FIM) was stabilized to 1.5 and the mean of trace of estimation error variance minimized to a value of 0.17. The modal information extracted from modal test conducted based on the optimized layout of sensors was in good agreement with the analytically obtained results. A maximum variation of 8.55% for modal frequency and 10.13% for damping ratio was observed. In addition to these two criteria, the study also uses an information entropy-based criterion to fine tune the number and position of sensors in the final sensor set. The proposed method is also compared with two other state-of-the-art optimization methods—Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Information Entropy Index (IEI) was used to compare the layout obtained from proposed method and state-of-the-art method. The IEI values for the layout based on the proposed method were 22–40% lower than those obtained using GA and PSO.

Flood is ranked as the deadliest natural disaster that has been experienced by the urban basins in the world. Its detrimental effects can be minimized by appropriate modeling, analysis and management methods. Such modeling and analysis techniques help in flood risk assessment predicting flood occurrence, aid in the emergency preparation for evacuation and reduce damage from the impact of floods. Numerous modeling techniques are available for analyzing flood events, of which HEC-HMS software is chosen for this explorative study because of its simplicity and as it is a freely available open-source software. The present study aims to develop a rainfall–runoff simulation model by generating peak flow and volume of the extreme rainfall event that occurred on 22 November 1999 in the ungauged Koraiyar basin located south of Tiruchirappalli City in South India. The hydrographs are generated for the basin by using specified hyetograph and frequency storm method to identify the best method to be adopted in the study. Digital elevation model processed with geographic information system (GIS) and HEC-Geo HMS, which is an extension of GIS, is used for the analysis. Using the terrain processing tools in ArcGIS, the basin delineation and parameters such as slope and river length are extracted from the basin. The data generated during the HEC-Geo HMS process are the hydrologic parameters of Koraiyar basin, and it is imported to HEC-HMS modeling for generating peak flow and volume. In the modeling process, HEC-HMS has three modules, namely transform, loss and base flow. SCS curve number and SCS unit hydrograph are used to determine the losses and transformation of rainfall into the runoff process in the present study. The SCS method is adopted because of its simplicity and requirement of limited data approach for modeling. The peak flow and volume prepared from the model are compared with the standard Nash–Sutcliffe values. The frequency storm method has a Nash value of 0.7, which is higher than the value obtained from the specified hyetograph process, and it is chosen as a better model for generating flood peak and volume for different return periods in the basin. It can therefore be adopted for other studies of similar basin conditions.

Health care is one of the most important facility and it helps to improve the quality of life and social welfare of modern society. Recent advances in the field of health geography have greatly improved our understanding of the role played by geographic distribution of health services in population health maintenance. This study presents a two stages methodology to evaluate the existing locations of healthcare facilities in Thiruverumbur block, Tiruchirappalli district of Tamil Nadu, India and includes to identify the optimal site for new healthcare facility. Firstly, the Spatial Accessibility index to healthcare facilities are measured using Three Step Floating Catchment Area (3SFCA) in a geospatial framework, considering three variables; namely, attractiveness of healthcare facilities, travel time or distance between the locations of the service centre and the residence, and population demand for healthcare facilities. This index would define the disparity region in the healthcare accessibility in the block. Secondly, the Multi-criteria decision analysis would be developed to find optimal sites for new healthcare facility in the deprived area. The analysis also includes road network analysis, to determine the closest facility and shortest route to these healthcare facilities from the population. The study is thus, recommended as a spatial decision support system for urban policy makers regarding accessibility of healthcare facilities in the urban and rural area.

Selecting a suitable site for urban development in a city is one of the critical issues in urban planning. This study illustrates the use of geographic information system (GIS) and multi-criteria evaluation (MCE) techniques for the selection of suitable sites for urban development in Tiruchirappalli, Tamil Nadu, India. Toposheet and CARTOSAT 1 satellite data were used to generate various thematic layers using ArcGIS software. Using these tools, several suitability factors including slope, soil, geology, road proximity, land use/land cover, depth to water table, distance from built-up area, geomorphology, and water quality map were evaluated. An analytical hierarchical process was used to rank the various suitability factors and the resulting weights were used to construct the suitability map layers. In doing so, the derived weights were used. Finally, a synthesised land suitability map was generated by combining these maps. The results of our research have been submitted to the regional authorities and will be used in strategic land-use planning.